Patch created using the following command line:
```bash
codespell polly --skip="*.pdf,polly/lib/External/*" --write-changes \
--ignore-words-list=couter,createor,distribues,doble,identty,indention,indx,olt,ore,padd,sais,te,theses
```
Even as the NPM has been in use by Polly for a while now, the majority
of the tests continue using the LPM passes. This patch ports the tests
to use the NPM passes (for example, by replacing a flag such as
-polly-detect with -passes=polly-detect following the NPM syntax for
specifying passes) with some exceptions for some missing features in the
new passes.
Relanding #90632.
Even as the NPM has been in use by Polly for a while now, the
majority of the tests continue using the LPM passes. This patch
ports the tests to use the NPM passes (for example, by replacing
a flag such as -polly-detect with -passes=polly-detect following
the NPM syntax for specifying passes) with some exceptions for
some missing features in the new passes. Additionally, the lit
substitution %loadPolly is replaced by the substitution of what
was %loadNPMPolly and %loadNPMPolly is removed.
The pattern matching optimization of Polly detects and optimizes dense general
matrix-matrix multiplication. The generated code is close to high performance
implementations of matrix-matrix multiplications, which are contained in
manually tuned libraries. The described pattern matching optimization is
a particular case of tensor contraction optimization, which was
introduced in [1].
This patch generalizes the pattern matching to the case of tensor contractions
using the form of data dependencies and memory accesses produced by tensor
contractions [1].
Optimization of tensor contractions will be added in the next patch. Following
the ideas introduced in [2], it will logically represent tensor contraction
operands as matrix multiplication operands and use an approach for
optimization of matrix-matrix multiplications.
[1] - Gareev R., Grosser T., Kruse M. High-Performance Generalized Tensor
Operations: A Compiler-Oriented Approach // ACM Transactions on
Architecture and Code Optimization (TACO). 2018. Vol. 15, no. 3.
P. 34:1–34:27. DOI: 10.1145/3235029.
[2] - Matthews D. High-Performance Tensor Contraction without BLAS // SIAM
Journal on Scientific Computing. 2018. Vol. 40, no. 1. P. C 1—C 24.
DOI: 110.1137/16m108968x.
Reviewed By: Meinersbur
Differential Revision: https://reviews.llvm.org/D114336
